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as well as funding acquisition and (global) outreach, if desired. International networking and collaborations are regarded as an integral part of the PhD research experience and are explicitly
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on the use of new Lyapunov-based deep learning methods. Such development includes: ideation, mathematical development, Lyapunov-based analysis, executing simulations and experiments, and disseminating research
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epidemiology. We seek a talented and enthusiastic person with experience in epidemiology, genetics or statistics. For more information about the center, see https://www.ntnu.edu/hunt/mce At HUNT MCE we use
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Master’s degree (or other equivalent experience). Suitable backgrounds for these PhD positions include, but are not limited to, power engineering, industrial engineering and operations research, mathematics
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organisations). Whilst some home working is acceptable, geographical proximity and willingness to be in a workplace environment are required. A professional qualification or training and experience in aspects
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expression and regulation Utilize genetic tools such as the CRISPR/Cas9 and Cre-LoxP system for genome engineering Assist with the design and execution of experiments in developmental biology Contribute
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. Basic biochemistry and molecular biology skillsets are required. We strongly encourage applications from candidates with advanced microscope working training. Rodent working experience, especially mouse
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interdisciplinary research team. We study tumor evolution and immune microenvironment adaptation by combining functional genomics, experimental model systems, patient samples, and computational biology (Brägelmann et
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Materials and Devices – Structure and Function of Materials (IMD-1) to establish a data-driven, experimentally grounded workflow for rapid microstructure-property optimization in steels. The PhD student will
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programme, please see DTU's rules for the PhD education . Assessment The ideal candidate will have solid background in experimental molecular biology combined with experience with microbial protein production